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Default It's amazing what you can find when you look.

Oooh look at all those lines.

DIGITAL WATERMARKING OF AUDIO SIGNALS USING A

PSYCHOACOUSTIC AUDITORY MODEL AND SPREAD SPECTRUM

THEORY

RICARDO A. GARCIA*, AES Member

School of Music Engineering Technology, University of Miami

Coral Gables, FL 33146, USA

A new algorithm for embedding a digital watermark into an audio

signal is proposed. It uses spread spectrum theory to generate a

watermark resistant to different removal attempts and a psychoacoustic

auditory model to shape and embed the watermark into the audio signal

while retaining the signal's perceptual quality. Recovery is performed

without knowledge of the original audio signal. A software system is

implemented and tested for perceptual transparency and data-recovery

performance.

0 INTRODUCTION

Every day the amount of recorded audio data and the possibilities to
distribute it (i.e. by the

Internet, CD recorders, etc) are growing. These factors can lead to an
increase in the illicit

recording, copying and distributing of audio material without respect to the
copyright or

intellectual property of the legal owners. Another concern is the tracking
of audio material over

broadcast media without the use of human listeners or complicated audio
recognition devices.

Audio watermarking techniques promise a solution to some of these problems.

The concept of watermarking has been used for years in the fields of still
and moving

images. The basic idea of a watermark is to include a special "code" or
information within the

transmitted signal. This code should be transparent to the user
(non-perceptible) and resistant

against removal attacks of various types.

In audio signals, the desired characteristics can be translated into:

- Not perceptible (the audio information should appear "the same" to the
average listener

before and after the code is embedded).

- Resistant to degradation because of analog channel transmission. (i.e. TV,
radio and tape

recording).

- Resistant to degradation because of uncompressed-digital media. (i.e. CD,
DAT and wav

files).

- Resistant to removal through the use of sub-band coders or psychoacoustic
models. (i.e.

MPEG, Atrac, etc).

The proposed algorithm generates a digital watermark (i.e. a bit stream)
that is spectrally

shaped and embedded into an audio signal. Spread spectrum theory is used in
the generation of

* Currently with the program in Media Arts & Sciences, Machine Listening
Group,

Massachusetts Institute of Technology (MIT), Cambridge, MA 02139 - 4307 USA.

2

the watermark. The strength of coded direct-sequence/binary-phase-shift
keying (DS/BPSK) is

used to create a robust watermark. The concepts are adapted to better deal
with audio signals in a

restricted audio bandwidth. A psychoacoustic auditory model is applied to
shape and embed the

watermark into the audio signal while retaining its perceptual quality for
the average listener.

A complete psychoacoustic auditory model algorithm is explained in detail.
This

information is useful for other applications involving auditory models. The
spread spectrum

encoding and decoding processes are then presented. The algorithm performs
an analysis of the

incoming signal and searches the frequency domain for "holes" in the
spectrum where the spread

spectrum data can be placed without being perceived by the listener. The
psychoacoustic

auditory model is used to find these frequency "holes."

After transmission, the receiver recovers the embedded spread spectrum
information and

decodes it in order to reconstruct the original bit stream (watermark).
There is no need for the

receiver to have access to the original audio signal.

The algorithm was implemented in a software system to create an encoder and
decoder, and

its performance was evaluated for diverse channels and audio signals. The
survival of the

watermark (number of correct bytes/second) was analyzed for different
configurations of the

encoding system. Each one of these configurations was tested for
transparency using an ABX

listening test and for different channels (i.e. AM Radio, FM stereo radio,
Mini Disc, MPEG layer

3, D/A - A/D conversion, etc).

1 PSYCHOACOUSTIC AUDITORY MODEL

An auditory model is an algorithm that tries to imitate the human hearing
mechanism. It uses

knowledge from several areas such biophysics and psychoacoustics.

From the many phenomena that occur in the hearing process, the one that is
the most important

for this model is "simultaneous frequency masking." The auditory model
processes the audio

information to produce information about the final masking threshold. The
final masking

threshold information is used to shape the generated audio watermark. This
shaped watermark is

ideally imperceptible for the average listener. To overcome the potential
problem of the audio

signal being too long to be processed all at the same time, and also extract
quasi-periodic

sections of the waveform, the signal is segmented in short overlapping
segments, processed and

added back together. Each one of these segments is called a "frame."

The steps needed to form a psychoacoustic auditory model are condensed in
Figure 1. The

first step is to translate the actual audio frame signal into the frequency
domain using the Fast

Fourier Transform. In the frequency domain the power spectrum, energy per
critical band and the

spread energy per critical band are calculated to estimate the masking
threshold. This masking

threshold is used to shape the "noise or watermark" signal to be
imperceptible (below the

threshold). Finally frequency domain output is translated into the time
domain and the next

frame is processed.

1.1 Short Time Fourier Transform (STFT)

The cochlea can be considered as a mechanical to electrical transducer, and
its function is to

make a time to frequency transformation of the audio signal. To be more
specific, the audio

information, in time, is translated in first instance into a
frequency-spatial representation inside

the basilar membrane. This spatial representation is perceived by the
nervous system and

translated into a frequency-electrical representation.

3

This phenomenon is modeled using the short time Fourier Transform (STFT).
The STFT uses

successive, overlapped windows from the time domain input signal.

1.2 Simultaneous Frequency Masking and Bark Scale

Simultaneous masking of sound occurs when two sounds are played at the same
time and one

of them is masked or "hidden" because of the other. The formal definition
says that masking

occurs when a test tone or "maskee" (usually a sinusoidal tone) is barely
audible in the presence

of a second tone or "masker." The difference in sound pressure level between
the masker and

maskee is called the "masking level."[ 1 ]

It is easier to measure the masking level for narrow band noise maskers
(with a defined

center frequency) and sinusoidal tone maskees. Figure 2 (a) and (b) display
some curves that

show the masking threshold for different narrow band noise maskers centered
at 70, 250, 1000

and 4000 Hz. The level of all the maskers is 60 dB. The broken line
represents the "threshold in

quiet." Average listeners will not hear any sound below this threshold.
Figure 2 (a) uses a linear

and (b) uses a logarithmic frequency scales.

The shape of all the masking curves is very different across the frequency
range in both

graphs. There are some similarities in the shape of the curves below 500 Hz
in the linear

frequency scale (a), and some similarities above 500 Hz in the logarithmic
frequency scale (b). A

more useful scale has been introduced that is known as "critical band rate"
or "Bark scale." The

concept of the Bark scale is based on the well-researched assumption [ 1 ]
that the basilar

membrane in the hearing mechanism analyzes the incoming sound through a
spatial-spectral

analysis. This is done in small sectors or regions of the basilar membrane
that are called "critical

bands." If all the critical bands are added together in a way that the upper
limit of one is the

lower limit of the next one, the critical band rate scale is obtained. Also
a new unit has been

introduced, the "Bark" that is by definition one critical band wide.

Figure 3 shows the same masking curves from Figure 2 in a Bark scale. Notice
that the shape

of the masking curves is almost identical across the frequency range.
Various approximations

may be used to translate frequency into a Bark scale [ 2 ]:

÷ ÷

ø

ö

ç ç

è

æ

÷ø

ö

çèæ

+

÷ø

ö

çè

= - æ -

2

1 1

7500

3.5tan

1000

0.76 *

13tan

f f

z ( 1 )

and [ 3 ]:

0.53

1960

26.81* -

+

=

f

f

z ( 2 )

where f is the frequency in Hertz and z is the mapped frequency in Barks.

Eq. ( 1 ) is more accurate, but the Eq. ( 2 ) is easier to compute. Figure 3
shows the excitation

level of several narrow band noises with diverse center frequencies in a
Bark scale.

1.3 Power Spectra

The first step in the frequency domain (linear, logarithmic or bark scales)
is to calculate the

power spectra of the incoming signal. This is calculated with:

{ } { }

2

2 2

( )

( ) Re ( ) Im ( )

w

w w w

Sw j

Sp j Sw j Sw j

=

= +

( 3 )

The energy per critical band, Spz(z) , is defined as:

4

å=

=

HBZ

LBZ

Spz z Sp j

w

( ) ( w) ( 4 )

Whe z = 1,2,.,total of critical bands Zt; LBZ and HBZ the lower and
higher frequencies in

the critical band z.

The power spectrum Sp(jw) and the energy per critical band Spz(z) are the
base of the

analysis in the frequency domain. They will be used to compute the spread
masking threshold.

1.4 Basilar Membrane Spreading Function

A model that approximates the basilar membrane spreading function, without
taking in

account the change in the upper slope is defined [ 3 ]:

B(z) =15.91+ 7.5(z + 0.474) -17.5 1+ (z + 0.474)2 ( 5 )

where z is the normalized Bark scale. Figure 4 shows B(z) .

The auditory model uses the information about the energy in each critical
band given by Eq. (

4 ) and uses Eq. ( 5 ) to calculate the spread masking across critical bands
Sm(z) . This is done

using:

Sm(z) = Spz(z) * B(z) ( 6 )

This operation is a convolution between the basilar membrane spreading
function and the total

energy per critical band. A true spreading calculation should include all
the components in each

critical band, but for the purposes of this algorithm, the use of the energy
per critical band

Spz(z) is a close approximation. Sm(z) can be interpreted as the energy per
critical band after

taking in account the masking occasioned by neighboring bands.

1.5 Masking Threshold Estimate

1.5.1 Masking Index

There are two different indexes used to model masking. The first one is used
when a tone is

masking noise (masker = tone, maskee = noise), and it is defined to be 14.5
+ z dB below the

spread masking across critical bands Sm(z) . In this case z is the center
frequency of the masker

tone using a bark scale. The second index is used when noise is masking a
tone (masker = noise,

maskee=tone), and is defined to be 5.5 dB below Sm(z) , regardless of the
center frequency [ 4 ].

1.5.2 Spectral Flatness Measure (SFM) and Tonality Factor a

The spectral flatness measure (SFM) is used to determine if the actual frame
is noise-like or

tone-like and then to select the appropriate masking index. The SFM is
defined as the ratio of the

geometric to the arithmetic mean of Spz(z) , expressed in dB as:

Zt

Zt

z

Zt

z

dB

Spz z

Zt

Spz z

SFM

1

1

1

( )

1

( )

10log10

ï ïþ

ï ïý

ü

ï ïî

ï ïí

ì

=

å

Õ

=

= ( 7 )

with Zt = total number of critical bands on the signal

5

The value of the SFM is used to generate the "tonality factor" that will
help to select the right

masking index for the actual frame. The tonality factor is defined in [ 3 ],
[ 4 ] as the minimum

of the ratio of the calculated SFM over a SMF maxima and 1:

÷ ÷ø

ö

ç çè

æ

= min , 1

dBmax

dB

SFM

SFM a ( 8 )

with SFM dB dB 60 max = - .

Therefore, if the analyzed frame is tone-like, the tonality factor a will be
close to 1, and if the

frame is noise-like, a will be close to 0. The tonality factor a is used to
calculate the masking

energy offset O(z), is defined as [ 3 ], [ 4 ]:

O (z) =a(14.5 + z) + (1-a)5.5 ( 9 )

The offset O(z)is subtracted from the spread masking threshold to estimate
the raw masking

threshold Traw(z) .

( ) ÷

ø

ö

çè

æ -

= 10

( )

log10 ( ) ( ) 10

O z

Sm z

Traw z ( 10 )

1.5.3 Threshold Normalization

The use of the spreading function B(z) increases the energy level in each
one of the critical

bands of the spectrum Sm(z) . This effect has to be undone using a
normalization technique, to

return Traw(z) to the desired level. The energy per critical band calculated
with Eq. ( 4 ) is also

affected by the number of components in each critical band. Higher bands
have more

components than lower bands, affecting the energy levels by a different
amount. The

normalization used [ 4 ] simply divides each one of the components of
Traw(z) by the number

of points in the respective band z P .

z P

Traw z

Tnorm z

( )

( ) = ( 11 )

Whe

z 1,2, .Zt

P number of points in each band z z

= ¼

=

1.5.4 Final Masking Threshold

After normalization, the last step is to take in to account the absolute
auditory threshold or

"hearing threshold." The hearing threshold varies across the frequency range
as stated in Zwicker

and Zwicker [ 1 ]. In the proposed auditory model the hearing threshold will
be simplified to use

the worst case threshold (the lowest). That is defined as a sinusoidal tone
of 4000 Hz with one bit

of dynamic range [ 4 ]. These values are chosen based on the data from
experimental research

that shows that the most sensitive range of the human ear is in the range of
2500 to 4500 Hz [ 1 ].

For a frequency of 4000 Hz, the measured sound intensity is 10-12 Watt/m2,
that equals a loudnes

of 0 phons at that frequency [ 12 ].The chosen amplitude (one bit) is the
smallest possible

amplitude value in a digital sound format. The hearing threshold is then
calculated with [ 4 ]:

TH = max(Pp( jw) ) ( 12 )

whe

( ) sin(2 4000 )

( ) power spectrum of the probe signal ( )

p t t

Pp j p t

p

w

=

=

6

The final threshold T(z) is:

T(z) = max(Tnorm(z),TH) ( 13 )

1.6 Noise Shaping Using the Masking Threshold

The objective of the auditory model is to find a usable masking threshold.
The final masking

threshold is always compared with the values of the power spectrum of the
signal Sp( jw) . This

can be interpreted as "below this threshold, the information is not relevant
for human hearing."

This means that if the frequency components that fall below the masking
threshold are removed;

the average listener will notice no difference between the original sound
signal and the altered

version.

Another very important consequence of this is that if these components are
not just discarded

but replaced with new components they will be, as before, inaudible for the
listener. This

assumes that the new components do not change the average energy
considerably in their critical

band. Let the frame with the new components be called N( jw) . The objective
is to use the final

masking threshold to select which components from Sp( jw) can be replaced
with components

from N( jw) . The components of N( jw) are shaped to stay below the final
masking threshold.

The final signal, that includes components from Sw( jw)and N( jw) , ideally
retains the

perceptual quality of the original signal for the average listener.

The following steps are used to remove the components from Sw( jw) , shape
the vector

N( jw) and mix them:

Calculate the "new" version of the sound signal (after removing some
components):

i

i

Sp j T z

Sw j Sp j T z

Swnew j

i

i i

i

z, according to component

1,2 number of components

0 ( ) ( )

( ) ( ) ( )

( )

w

w

w w

w

= K

î í ì



³

=

( 14 )

Remove the unneeded components in the N( jw) vector:

i

i

N j Sp j T z

Sp j T z

Nnew j

i i

i

i

z, according to component

1,2 number of components

( ) ( ) ( )

0 ( ) ( )

( )

w

w w

w

w

= K

î í ì



³

=

( 15 )

Calculate the power spectrum of Nnew( jw) :

2 Nnewp( jw) = Nnew( jw) ( 16 )

and then, the energy per critical band:

å=

=

HBZ

LBZ

Nnewpz z Nnewp j

w

( ) ( w) ( 17 )

Whe z = 1,2,.,total of critical bands Zt; LBZ and HBZ the lower and
higher frequencies in

the critical band z.

7

The shaping is done applying a factor z F to each critical band. These
factors are given by:

( )

LBZ HBZ z

z Zt

Nnew j

T j

F A z

to for each band

1,2

max ( )

( )

=

=

=

w

w

w

K

( 18 )

The coefficient A is used as the "gain of the noise signal". Varies from 0
to 1 and weights the

embedded noise below the threshold of masking. The factors z F are applied
using:

LBZ HBZ z

z Zt

Nfinal j Nnew j Fz

to for each band

1,2

( ) ( )

=

=

=

w

w w

K ( 19 )

The final step is to mix both spectrums, the altered Swnew( jw) and the
shaped Nfinal( jw) to

form the composite signal OUT( jw) :

OUT( jw) = Swnew( jw) + Nfinal( jw) ( 20 )

2 SPREAD SPECTRUM

One of the requirements of a watermarking algorithm is that the watermark
should resist

multiple types of removal attacks. A removal attack is considered as
anything that can degrade or

destroy the embedded watermark. Another factor to be considered is that the
masking threshold

of the actual audio signal determines the embedding of the watermark,
because the watermark is

embedded in the "spare components" found using the psychoacoustic auditory
model. From this

point of view, the watermark has to be the least intrusive to the audio
signal, and therefore, the

actual audio data can be seen as the main obstacle for a good watermarking
algorithm. This is

because the audio will use all the needed bandwidth and the watermark will
use what is left after

the auditory model analysis.

The desired watermarking technique should be resistant to degradation
because of:

- The used transmission channel: analog or digital.

- High-level wide-band noise (in this case, the "noise" is the actual audio
signal). This is

often related as "low signal to noise ratio".

- The use of psychoacoustic algorithms on the final watermarked audio.

A communication theory technique that meets the requirements is the "spread
spectrum

technique", as described thoroughly in Simon et al. [ 5 ] and Pickholtz et
al.

[ 6 ]. "Spread spectrum is a means of transmission in which the signal
occupies a bandwidth in

excess of the minimum necessary to send the information; the band spread is
accomplished by

means of a code which is independent of the data, and a synchronized
reception with the code at

the receiver is used for despreading and subsequent data recovery." [ 6 ]

In the following analysis, the process of generating a watermark that will
be embedded in an

audio signal is expressed in spread spectrum terminology. The original audio
signal will be

called "noise" and the bit stream that conforms the watermark sequence will
be the data signal.

The watermark sequence is transformed in a watermark audio signal and then
the audio signal

(noise) is added to it. This process of adding noise to a channel or signal
is called "jamming."

The objective of a jammer in a communication system is to degrade the
performance of the

transmission, exploiting knowledge of the communication system. In the
watermark algorithm

8

the audio signal (i.e. music) is considered the jammer, and it has much more
power than the

transmitted bit stream (watermark).

2.1 Basic Concepts

The primary challenge that a receiver must overcome is intentional jamming,
especially if the

jammer has much more power than the transmitted signal. Classical
communications theoretical

investigations about additive white Gaussian noise help to analyze the
problem. White Gaussian

noise is a signal which has infinite power spread uniformly over all
frequencies; but even under

these circumstances communication can be achieved due to the fact that on
each of the "signal

coordinates" the power of the noise component is limited (not infinite).
Therefore, if the noise

component in the signal coordinates is not too large, communication can be
made. This is usually

applied in a typical narrow-band signal, where just the noise components in
the signal bandwidth

are taken into account as possible factors that can do harm to the
communication. With this

knowledge, the best strategy to combat intentional jamming is to select
signal coordinates where

the jammer to signal ratio is the smallest possible.

Assume a communication link with many signal coordinates available to choose
from, and

only a small subset of these is used at any time. If the jammer can not
determine which subset is

being used, it is forced to jam all the coordinates and therefore, all its
power will be distributed

among all the coordinates, with little power in each of them. If the jammer
chooses to jam only

some of the coordinates, the power over each of them is larger, but the
jammer lacks the

knowledge of which coordinates to jam. The protection against the jammer is
enhanced, as more

signal coordinates are available to choose from.

Having a signal of bandwidth W and duration T, the number of coordinates
available is given

by:

î í ì

@

non - coherent signals

2 coherent signals

WT

WT

N ( 21 )

T is the time used to send a standard symbol. To make N larger when T is
fixed, two techniques

can be applied:

§ Direct sequence spreading (DS): this is the selected approach in this
algorithm.

§ Frequency hopping (FH)

The signals created with these techniques are called "spread spectrum
signals."

2.1.1 Models and Fundamental Parameters

The basic system is shown in Figure 5, with the following parameters:

Wss = Total spread spectrum signal bandwidth available

Rb = Data rate ( bits / second )

S = Signal power (at the input of the receiver)

J = Jammer power (at the input of the receiver)

Wss is defined as the total available spread spectrum bandwidth that could
be used by the

transmitter, but it is not guaranteed that it will be used during the actual
transmission. Neither is

it guaranteed that the spectrum will be continuous. Rb is the uncoded bit
data rate used during

transmission. The signal and the jammer powers S and J are the averaged
power at the receiver.

This does not change even if the jammer and/or the signal are pulsating.

9

2.1.2 Jammer Waveforms

The number of possible jammer waveforms that a jammer can apply to a
communication

system is infinite. The principal types include:

- Broadband Noise Jammer: Spreads Gaussian noise of a total power J evenly
over the total

frequency range of the spread bandwidth Wss.

- Partial Band Noise Jammer: Spreads noise of total power J evenly over a
frequency range of

bandwidth WJ, which is contained in the total spread bandwidth Wss. r is the
fraction of the

total spread spectrum bandwidth that is being jammed.

- Pulse Jammer: Transmits the jammer waveform during a fraction r of the
time, the average

power is J, but the peak power during transmission is higher.

2.2 Coherent Direct-Sequence Systems

Coherent direct-sequence systems use a pseudorandom sequence and a modulator
signal to

modulate and transmit the data bit stream. The main difference between the
uncoded and coded

versions is that the coded version uses redundancy and "scrambles" the data
bit stream before the

modulation is done and reverses the process at the reception. The
watermarking algorithm uses

the coded scheme, but the uncoded is studied because is easier to understand
and is the

foundation of the coded scheme.

2.2.1 Uncoded Direct-Sequence Spread Binary Phase-Shift-Keying

Uncoded Direct-Sequence Spread Binary Phase-Shift-Keying is known as Uncoded

DS/BPSK. It may be explained with a simple example. BPSK signals are often
expressed as:

( 1) , integer

2

( ) 2 sin 0

£ + =

úû

ù

êë

= é +

nT t n T n

d

s t S t

b b

np

w

( 22 )

where

Tb is the data bit time ÷ ÷

ø

ö

ç çè

æ

b R

1

{ } n d is the sequence of data bits, with the possible values of 1 or -1;

and equal probability of occurrence.

Eq. ( 22 ) can be expressed as:

( 1) , integer

( ) 2 cos( ) 0

£ + =

=

nT t n T n

s t d S t

b b

n w

( 23 )

BPSK can be seen as phase modulation in Eq.( 22 ) or amplitude modulation in
Eq. ( 23 ). The

spectrum of a BPSK signal is usually of the form shown in Figure 6. This is
a (sin 2 x) x2

function, and the first null bandwidth is b 1 T . This shows the minimum
bandwidth needed to

transmit the signal s(t) and to recover it at the receiver.

Spread spectrum theory requires the signal to be spread over a larger
spectrum than the

minimum needed for transmission. The spreading of the direct sequence is
done using a

pseudorandom (PN) binary sequence {c}. The values of this sequence are 1
or -1 and its speed is

N times faster than the{d} data rate. The time, Tc, of each bit on a PN
sequence is known as a

"chip" and is given by:

10

N

T

T b

c = ( 24 )

The direct sequence spread spectrum signal has the form:

[ ]

integer

0,1,2 1

( 1)

2 cos( )

( ) 2 sin / 2

0

0

=

= -

+ £ + +

=

= -

+

+

n

k N

nT kT t nT k T

d c S t

x t S t d c

b c b c

n nN k

n nN k

K

w

w p

( 25 )

The signal is very similar to the common BPSK, except that the bit rate is N
times faster and the

power spectrum is N times wider, as shown in Figure 7. The processing gain
is given by:

N

R

W

PG

b

= SS = ( 26 )

WSS is the direct sequence spread spectrum bandwidth

c b T

N

T

1 1 = .

If the data function is defined as:

integer

( ) , ( 1)

=

= £ +

n

d t d nT t n Tn b b ( 27 )

and the PN sequence is:

integer

( ) , ( 1)

=

= £ +

k

c t c kT t k Tk c c ( 28 )

Eq. ( 25 ) can be expanded as:

[ ]

( ) ( ) 2 cos( )

( ) 2 sin ( ) ( ) / 2

0

0

c t d t S t

x t S t c t d t

w

w p

=

= +

( 29 )

Figure 8 shows the block diagram for the normal DS/BPSK modulation; and
Figure 9 shows

an equivalent model used in the next step of the analysis. Figure 11 shows
the signals d(t) and

c(t) and Figure 12 shows c(t)d(t) with N=6. From Figure 9, the equivalent
form of x(t) is given

by:

x(t) = c(t)s(t) ( 30 )

Where ( ) ( ) 2 cos( ) 0s t = d t S w t ( 31 )

This is the original BPSK signal. The property:

c2 (t) = 1 for all t ( 32 )

is the key point exploited to "recover" the original BPSK signal:

c(t)x(t) = s(t) ( 33 )

If the receiver possesses a copy of the PN sequence and can synchronize the
local copy with

the received signal x(t), it is able to de-spread the signal and recover the
transmitted data.

11

2.2.1.1 Constant Power Broadband Noise Jammer

A jammer, J(t), with constant power J is shown in Figure 10. The system is
also assumed to

have no noise from the transmission channel. An ideal BPSK demodulator is
assumed after the

received signal y(t) is multiplied by the PN sequence. The channel output
is:

y(t) = x(t) + J (t) ( 34 )

This is multiplied by the PN sequence c(t):

( ) ( ) ( )

( ) ( ) ( ) ( )

( ) ( ) ( )

s t c t J t

c t x t c t J t

r t c t y t

= +

= +

=

( 35 )

This term shows the original BPSK signal plus a noise given by c(t)J(t). The
output of the

conventional BPSK detector is then:

r d E n b = + ( 36 )

whe d is the data bit for the actual Tb second interval.

Eb=STb is the bit energy.

n is the equivalent noise component.

n is further defined as:

= ò b

b

T

c t J t t dt

T

n

0

( ) ( )cos( 0 )

2 w ( 37 )

The usual decision rule for BPSK is:

î í ì

- £



=

1, if 0

^ 1, if 0

r

r

d ( 38 )

2.2.2 Coded Direct Sequence Spread Binary Phase-Shift-Keying

Several types of coding techniques can be used that provide extra gain and
force the worst

case jammer to be a constant power jammer. Coding techniques usually require
the data rate to

be decreased or the bandwidth increased because of the redundancy inherent
to the coding. In

spread spectrum systems, coding does not require an increase of the
bandwidth or decrease of the

bit rate. These properties can be seen in a simple example. If k=2 (constant
length) the rate is

R=1/2 bits per coded symbol of convolutional code. For each data bit of the
sequence {d}, the

encoder generates two coded bits. For the kth transmission interval, the two
data bits a

ak = (ak1,ak 2) ( 39 )

whe

î í ì -

¹

=

=

=

-

-

1

1

2

1

1

1

k k

k k

k

k k

d d

d d

a

a d

( 40 )

If Tb is the data bit time, each coded bit time is given by:

2

b

s

T

T = ( 41 )

Defining:

integer

( 1/ 2) ( 1)

( 1/ 2)

( )

2

1

=

î í ì

+ £ +

£ +

=

k

a k T t k T

a kT t k T

a t

k b b

k b b

( 42 )

12

In Figure 11 the uncoded data signal d(t), the PN sequence c(t) and the
coded signal a(t) are

shown for N=6. In Figure 12 the multiplicated signals d(t)c(t) and a(t)c(t)
are shown. With

ordinary BPSK, the coded signal a(t) would have twice the bandwidth of the
uncoded signal; but

after spreading with the PN sequence, the final bandwidth is the same as the
original. One of the

simplest coding schemes is the "repeat code." It sends m bits with the same
value, d, for each

data bit. The rate is then R=1/m bits per coded symbol. In this case, the
resulting coded bits a

( , , , ) 1 2 m a = a a K a ( 43 )

Whe a d i m i = =1,2,K, ( 44 )

Also, each coded bit ai has a transmission time of:

m

T

T b

s = ( 45 )

It is very important to note that if mN, the bandwidth of the spread signal
does not change. The

complete coded DS/BPSK system is shown in Figure 13.

The interleaver scrambles the bits in time at the transmission, and the
deinterleaver

reconstructs the data sequence at the receiver. After the interleaver, the
signal is BPSK

modulated and then multiplied by the PN sequence. At this point the
transmitted DS/BPSK

signal looks like the one in Eq. ( 30 ).

x(t) = c(t)s(t)

where s(t) is the common BPSK (with coding). The input at the receiver is
the same as that in

Eq. ( 34 ):

y(t) = x(t) + J (t)

After multiplication with c(t) (de-spreading), it becomes Eq. ( 35 ):

r(t) = s(t) + c(t)J (t)

The output of the detector after the de-interleaver is given by:

i m

Z n

m

E

r a i i

b

i i

= 1,2,K,

= +

( 46 )

where n1,n2,.nm are independent zero mean Gaussian random variables with
variance NJ/(2r). r

is the fraction of time that the pulse jammer is on, and Zi is the jammer
state:

î í ì

=

0 jammer off during transmission

1 jammer on during transmission

i

i

i a

a

Z ( 47 )

With probability equal to:

{ }

{ } r

r

= = -

= =

Pr 0 1

Pr 1

i

i

Z

Z

( 48 )

2.2.2.1 Interleaver and Deinterleaver

The idea of using an interleaver to scramble the data bits at transmission
and a deinterleaver

to unscramble the bits at reception causes the pulse jamming interference on
each affected data

bit to be independent from each other. In the ideal interleaving and
deinterleaving process, the

13

variables Z1,Z2,.,Zm become independent random variables. Assume that there
is no interleaver

and/or deinterleaver in the system shown in Figure 13. The output of the
channel is given by:

i m

Zn

m

E

r d i

b

i

= 1,2,K,

= +

( 49 )

and because there is no interleaver/deinterleaver:

i m

Z Z

a d

i

i

=1,2,K,

=

=

( 50 )

Also, it is assumed that the jammer was on during the whole data bit
transmission Tb. Because

there is no interleaver/deinterleaver, the optimum decision rule is:

å

å

=

=

= +

=

m

i

b i

m

i

i

d mE Z n

r r

1

1 ( 51 )

Eq. ( 38 ) is used as a decision rule:

î í ì

- £



=

1, if 0

^ 1, if 0

r

r

d

This bit error probability is the same for uncoded DS/BPSK; this means that
without a

interleaver/deinterleaver, there is no difference between uncoded systems
and simple repeat code

systems. Therefore, the use of a interleaver/deinterleaver is mandatory in
order to achieve a good

error probability measure against a pulse jammer.

Selection of the decision technique that determines the value of the coded
bits {r} requires

knowledge about the state of the channel. With an ideal
interleaver/deinterleaver, the output of

the channel is given by Eq. ( 46 ):

i m

Z n

m

E

r a i i

b

i i

= 1,2,K,

= +

where Z1,Z2,.,Zm and n1,n2,.,nm are considered to be independent random
variables. The

decoder takes r1,r2,.,rm and finds d1,d2,.,dm with possible values of 1
or -1. This analysis is

valid only for the instances where the state of the channel is unknown
(there is no information

regarding the state of the jammer signal).

2.2.2.2 Hard Decision Decoder

The hard decision decoder performs a binary decision on each coded bit
received:

i m

r

r

d

i

i

i

1,2, ,

1 0

^ 1 0

= K

î í ì

- £



=

( 52 )

The final decision in decoding the transmitted bit is:

14

ï ïî

ï ïí

ì

- £



=

å

å

=

=m

i

i

m

i

i

k

d

d

d

1

1

1 ^ 0

1 ^ 0

^ ( 53 )

2.2.2.3 Interleaver Matrix

The interleaving techniques will improve the performance in pulse jammer
environments

because it makes the noise components become statistically independent
variables. A block

interleaver with depth I=5 and interleaver span H=15 is shown in Figure 14.
The coded symbols

are written to the interleaver matrix along columns, while the transmitted
symbols are read out of

the matrix along rows. If the coded symbol sequence is x1,x2,x3. the
sequence that comes out of

the interleaver matrix is x1,x16,x31,x46,x61,. . At the receiver, the
deinterleaver performs the

inverse process, writing symbols into rows and reading them by columns. A
jamming pulse of

duration b symbols, with b £ I will result in these jammed symbols at the
deinterleaver output to

be separated at least by H symbols.

2.3 Synchronization of Spread-Spectrum Systems

Because a pseudorandom sequence PN is used at the transmitter to modulate
the signal, the

first requirement at the receiver is to have a local copy of this PN
sequence. The copy is needed

to de-spread the incoming signal. This is done by multiplying the incoming
signal by the local

PN sequence copy. To accomplish a good de-spreading, the local copy has to
be synchronized

with the incoming signal and the PN sequence that was used in the spreading
process.

The process of synchronization is usually performed in two steps: first, a
coarse alignment of

the PN sequence is done with a precision of less than a "chip." This is
called "PN acquisition."

After this, a fine synchronization takes care of the final alignment and
corrects the small

differences in the clock during transmission. This is called "PN tracking."
Theoretically,

acquisition and tracking can be done in the same step with a structure of
matched filters or

correlators searching with high resolution the incoming signal and comparing
it with the local

PN sequence.

2.3.1 Fast Fourier Transform (FFT) Scalar Filters

These filters are implemented in the frequency domain, and they use the Fast
Fourier

Transform (forward and backward). They work over a set of N samples (usually
in the frequency

domain) [ 7 ]. The block diagram of an adaptive digital filter is shown in
Figure 15.

Whe s(n) is the input signal

n(n) is the noise (unwanted) signal

r(n) is the input to the filter

R(m) is the frequency representation of the signal (n)

H(m) is the transfer function of the filter

C(m) is the output (in frequency domain) after the filter is applied

G(m) is the transfer function of the post-processing filter

P(m) is the output after the post-processing filter

p(n) is the output signal in the time domain

The following relationships are given:

15

( ) FFT ( ( ))

( ) ( ) ( )

( ) ( ) ( )

( ) FFT( ( ))

( ) ( ) ( )

p n 1 P m

P m G m C m

C m H m R m

R m r n

r n s n n n

= -

=

=

=

= +

( 54 )

2.3.1.1 High-resolution Detection FFT Scalar Filter

The high-resolution detection filter outputs a peak when the desired signal
s(n) and noise

n(n) are applied to it. The transfer function is given by:

2 2 ( ) ( )

*( )

( )

S m N m

S m

H m

+

= ( 55 )

This version of high-resolution detection assumes that the noise and the
signal are uncorrelated

(orthogonal). The output of this filter C(m) must be transformed to the time
domain to detect the

level and the position of the peak on the output vector c(n). This position
can be interpreted as

the exact point where the desired signal starts within the processed set of
samples N.

2.3.1.2 Adaptive Filtering

Adaptive filters require a learning process and use adaption techniques to
form the transfer

function of the desired filter H(m). The components of the transfer function
are updated

periodically with actual values taken from the signal or with estimates made
using stored data.

The class 1/3 high-resolution detection filter is given by [ 7 ]:

2 ( )

*( )

( )

R m

S m

H m = ( 56 )

where S*(m) is the conjugate of the spectrum of the desired signal to detect
and R(m) is the

magnitude of the spectrum of the actual input of the system.

The expression R(m) is used to denote the "smoothing" process. This process
is done to

estimate the average spectrum of the signal plus noise from the actual input
of the system. The

smoothing used is called "inner block averaging" or "frequency domain
averaging" and it is

defined as:

or ( ) ( )

( ) ( )

2

1

( )

r r t b t

R j R j B j

b =

= w * w

p

w

( 57 )

The frequency averaging window B(jw) is convolved with the spectrum of the
input signal. This

is equivalent to a temporal weighting of the input r(t) by b(t) in the time
domain. The window is

usually selected to be a percentage of the input vector length.

3 PROPOSED SYSTEM

Different systems have been applied to watermarking of audio signals. All of
them are

classified as "steganographic systems" because they deal with the concept of
hiding data within

the signal. Boney et al. [ 23 ] proposed a system where a PN sequence was
filtered using a filter

that approached the masking characteristics of the human auditory system in
the frequency and

16

time domains. Some other techniques have been imported from the fields of
video and still

image watermarking. Cox [ 24 ] proposes a multiplatform system capable of
extract a

pseudorandom sequence without the use of the original unwatermarked data.

The watermarking algorithm proposed in this paper mixes the psychoacoustic
auditory model

and the spread spectrum communication technique to achieve its objective. It
is comprised of

two main steps: first, the watermark generation and embedding and second,
the watermark

recovery. The watermark generation and embedding process is shown in Figure
16. A bit stream

that represents the watermark information is used to generate a noise-like
audio signal using a set

of known parameters to control the spreading. At the same time, the audio
(i.e. music) is

analyzed using a psychoacoustic auditory model. The final masking threshold
information is

used to shape the watermark and embed it into the audio. The output is a
watermarked version of

the original audio that can be stored or transmitted.

The watermark recovery is shown in Figure 17. The input is the watermarked
audio after

transmission (i.e. music + noise, low quality, etc). An auditory
psychoacoustic model is used to

generate a residual. At the same time as the known parameters are used to
generate the header of

the watermark. Using an adaptive high-resolution filter, all the residual is
scanned to find all the

occurrences of the known header and therefore the initial position of each
possible watermark.

After this, the same known parameters used to generate the header are used
to de-spread and

recover the watermark.

3.1 WATERMARK GENERATION AND EMBEDDING

3.1.1 WATERMARK GENERATION

The objective of the watermark generation is to generate a watermark audio
signal x(t) that

contains the watermark bit stream data. This watermark signal can be
transmitted and then

processed for data recovery. The technique used to generate the watermark
signal x(t) is "coded

DS/BPSK spread spectrum." The process is condensed in Figure 18.

Whe {w} is the original digital bit stream(watermark)

m is the repetition code factor

{ } R w is the watermark after the coding process (repeat code)

I,H = width and length of the interleaver matrix

{ } I w is the watermark after the interleaver process

{header}= is the header sequence

{ } { } { } I d = header + w = sequence to be spread and transmitted

f0 = frequency used by the BPSK modulator

The process can be explained with a simple example: Let {w} be the watermark
bit stream.

All the bit streams used are bipolar (value 1 or -1). Defining {w}with a
length of 16 bits as the

sequence:

{w}= { 1 1 -1 1 -1 -1 1 -1 1 1 -1 1 1 1 -1 -1}

Using Eq. ( 43 ) to generate the repeat code, and choosing m=3, the { } R w
sequence is:

17

{ }

1 1 1 1 1 1 1 1 1 1 1 1 }

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

{ 1 1 1 1 1 1 1 1 1 1 1 1

- - - - - -

- - -

- - - - - - - - -

= - - - R w

The next step is to perform interleaving. To do this, the values of the
interleaving matrix are

chosen; in this case, I=5, H=10, (see Figure 14). The resulting matrix is
shown in Figure 19. The

last two spaces are padded with 1's. Using the interleaving matrix, the
output sequence { } I w is:

{ }

1 1 }

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

{ 1 1 1 1 1 1 1 1 1 1 1 1

- - -

- - - - - - -

- - - - - - -

= - - - - I w

The selected header is a sequence usually composed by 1's.

{header}= {1 1 1 1 1 1 1 1 1 1}

The final data sequence {d} is obtained concatenating the {header} and the
{ } I w :

{ } { } { }

{ }

1 1 1 1 1 1 1 1 1 1 1 1 }

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

{ 1 1 1 1 1 1 1 1 1 1 1 1

- -

- - - - - - -

- - - - - -

- - - - - -

=

= +

d

d header wI

The PN sequence {c} can be generated by any means. Usually this is done
using a

pseudorandom number generator. In this case, the PN sequence is assumed to
be long enough to

spread a complete bit stream (header and data) without repeating any portion
of it. The important

factor is that the transmitter and the receiver must have a copy of the
whole PN sequence{c}.

This sequence is ideally uncorrelated with the {d} sequence, and has the
form:

{c}= { 1 -1 1 1 -1 -1 1 -1 1 1 -1 1 K}

3.1.1.1 Spread Spectrum Parameter Selection

Audio signals are usually considered to be baseband signals [ 21 ]. The
described spread

spectrum technique can be applied to passband systems (with f00) or
baseband systems (f0=0)

without losing generality. The selection of all the parameters is based on
the considerations of

how the overall watermarked audio signal will be transmitted or stored. The
frequency response

of those systems determines which frequencies are likely to be present at
the receiver. Let a

baseband bandlimited signal, with no modulation (f0=0) have the magnitude
spectrum shown in

Figure 20. With amplitude modulation (f00), the spectrum will have the form
shown in Figure

21. FS is the sampling frequency of the system. To avoid aliasing because of
the use of

modulation, the modulation frequency should be:

18

Rc

FS

Rc £ f £ -

2 0 ( 58 )

If a system possesses a lower frequency limit LF and/or an upper frequency
limit HF, the

modulation frequency f0 have to be selected in a way that the sidebands fall
between the lower an

upper limits, as shown in Figure 22. If a sideband falls outside of these
limits, aliasing or data

loss could result. Taking into account, the selection of parameters should
be done using:

2

0,

0

FS

LF HF

LF Rc f HF Rc

³ £

+ £ £ -

( 59 )

The parameters selected must satisfy Eq. ( 58 ) and Eq. ( 59 ), along with
the following

relationships:

Rd = is the data bits per second

m = is the repetition code factor

N = is the spreading factor, Eq. ( 26 )

Rb = Rd*m is the coded bits per second

Tb = 1/Rb is the time of each coded bit

Rc=N*Rb is thePN sequence bits per second

Tc=Tb/N is the time of each PN bit or "chip"

Assuming a frequency response similar to FM Radio [ 22 ] with LF = 50 Hz and
HF = 15000

Hz, for the actual example, a set of spread spectrum parameters that satisfy
all the requirements

is:

N = 3

m = 3

Rd = 100 bits/sec

Rb = 300 bits/sec

Rc = 900 bits/sec

f0 = 3500 Hz

Note that N and m are selected with small values for this example. The
modulation is done using

Eq. ( 31 ):

( ) ( ) 2 cos( ) 0s t = d t S w t

The spreading is done using Eq. ( 30 ):

x(t) = c(t)s(t)

The output of the system is the watermarked audio waveform x(t) shown in
Figure 23.

3.1.2 FRAME SEGMENTATION

To overcome the potential problem of the audio signal or the watermark
signal being too

long to be processed using a single FFT, the signal is segmented in short
overlapping segments,

processed and added back together [ 8 ]. Another consideration for the
watermark algorithm is

that the audio signal has to be longer than the watermark signal. Therefore,
the watermark can be

repeated several times during the duration of the audio signal. This
redundancy is one of the

important features in the watermarking algorithm. Figure 24 shows audio and
watermark signals

that will be segmented. The watermark is repeated several times. If the
total length of the audio

signal is LENGTH samples, the desired length of the analysis frame is BLOCK
samples, and the

19

overlap between consecutive frames is OVERLAP samples, the total number of
FRAMES is

given by:

BLOCK OVERLAP

LENGTH OVERLAP

FRAMES

-

-

= ( 60 )

In Figure 24 two equal length frames were selected to be processed. One from
the audio

signal and the other from the respective point in the watermark signal. The
last frame is zeropadded

if it is shorter than BLOCK samples. These padded samples are discarded in
post

processing. From this point on, all processes described are applied to the
audio or watermark

signal frames, not the entire signal.

3.1.3 FREQUENCY REPRESENTATION

The Short Time Fourier Transform (STFT) is used to acquire a frequency
representation of

the actual frames. Before doing the STFT, a Hamming window is applied to
both signals [ 7 ], [ 8

]. This improves the representation of the signal in the frequency domain
reducing the leakage. If

s(t) is the actual audio signal frame and x(t) the actual watermark signal
frame, then the

windowing is done using:

sw(t) = s(t)w(t) ( 61 )

xw(t) = x(t)w(t) ( 62 )

The Hamming window is defined as:

sampling period

( ) ( )

1,2

2

( ) 0.54 0.46cos

=

=

=

÷ø

ö

çè

= + æ

T

w t w nT

n BLOCK

BLOCK

n

w n

K

p

( 63 )

The frequency representation of the audio frame is:

Sw( jw) = FT{sw(t)} ( 64 )

and the watermark frame:

Xw( jw) = FT{xw(t)} ( 65 )

The power spectra is found using Eq. ( 3 ):

2 Sp( jw) = Sw( jw) ( 66 )

The indices of the actual frequency representations have to be mapped to the
Bark scale.

Once this index mapping is done, the representation in the critical band
scale is formed by

mapping the components to the respective position on the critical band axis.
The relationship

between each component index, i, and the corresponding frequency, fi, that
it represents is given

by:

Sampling Frequency

2

1,2

( 1) *

=

=

-

=

FS

BLOCK

i

BLOCK

i FS

fi

K

( 67 )

20

The relationship between each frequency fi and the bark scale or critical
band scale zI is found

using Eq. ( 1 ):

÷ ÷

ø

ö

ç ç

è

æ

÷ø

ö

çè

æ + ÷

ø

ö

çè

= - æ -

2

1 1

7500

3.5tan

1000

0.76*

13tan i i

i

f f

z

This relationship between each component index i and the frequency fi or
critical band zi that it

represents can be calculated at the beginning of the algorithm and stored in
a table. The energy

per critical band is calculated using Eq. ( 4 ):

å=

=

HBZ

LBZ

Spz z Sp j

w

( ) ( w)

Whe z = 1,2,.,total of critical bands Zt; LBZ and HBZ the lower and
higher frequencies in

the critical band z. Figure 25 (a) shows the original audio frame s(t) in
the time domain and the

shape of the Hamming window w(t); (b) shows the sw(t) frame after the
windowing process; (c)

shows the magnitude of Sw( jw) , and (d) shows the power spectrum Sp( jw)
and the energy per

critical band Spz(z) .

3.1.4 BASILAR MEMBRANE SPREADING FUNCTION

The basilar membrane spreading function determines how much of the energy of
each critical

band is contributed to the neighboring bands. The spreading function B(z) is
calculated using Eq.

( 5 ):

K 2, 1,0,1,2K

15.91 7.5( 0.474) 17.5 1 ( 0.474)2

= - -

= + + - + +

k

B k k k

The spreading across bands is computed by the convolution of the spreading
function B(z) and

the energy per critical band Spz(z) ,using Eq. ( 6 ):

Sm(z) = Spz(z) * B(z)

Figure 26 (a) shows the energy per critical band Spz(z) , (b) shows the
spreading function B(z)

for 9 points, and (c) shows the spread energy per critical band Sm(z).

3.1.5 MASKING THRESHOLD ESTIMATE

The Spectral Flatness Measure (SFM) of the actual audio frame Sw( jw) is
taken using

Eq. ( 7 ):

Zt

Zt

z

Zt

z

dB

Spz z

Zt

Spz z

SFM

1

1

1

( )

1

( )

10log10

ï ïþ

ï ïý

ü

ï ïî

ï ïí

ì

=

å

Õ

=

=

with Zt = total number of critical bands in each frame

The energy per critical band Spz(z) is used rather than spread energy per
critical band Sm(z)

to avoid false results due to smoothing of the signal. The tonality factor a
is then calculated

using Eq. ( 8 ):

÷ ÷ø

ö

ç çè

æ

= min ,1

dB max

dB

SFM

SFM a

21

with SFM dB dB 60 max = - .

The masking energy offset O(z) is then calculated using Eq. ( 9 ):

O(z) =a(14.5 + z) + (1-a)5.5

The raw masking threshold, Traw(z), is calculated with Eq. ( 10 ):

( ) ÷

ø

ö

çè

æ -

= 10

( )

log10 ( ) ( ) 10

O z

Sm z

Traw z

The raw masking threshold is normalized using Eq. ( 11 ):

z P

Traw z

Tnorm z

( )

( ) =

whe

z 1,2, .Zt

P number of points in each band z z

= ¼

=

To calculate the final masking threshold T it is necessary to first
calculate the hearing

threshold (or threshold in quiet) TH. It is defined as a sinusoidal tone of
4000 Hz with one bit of

dynamic range. Using Eq. ( 12 ):

TH = max(Pp( jw) )

Whe

( ) sin(2 4000 )

( ) power spectrum of the probe signal ( )

p t t

Pp j p t

p

w

=

=

Then the final masking threshold T is calculated using Eq.( 13 ):

T(z) = max(Tnorm(z),TH)

with: z=1,2,..Zt

Figure 27 (a) shows the raw masking threshold Traw(z) and (b) shows the
normalized

threshold Tnorm(z).

3.1.6 WATERMARK SPECTRAL SHAPING

The final masking threshold T is used to determine which components of the
audio signal

Sw( jw) can be removed without affecting the perceptual quality of the
signal. The power

spectrum Sp( jw) is compared against the final masking threshold T. The
components that fall

below it are removed in Sw( jw) . The new frame with only the components
above the threshold

is called Swnew( jw) . Eq. ( 14 ) is used:

i

i

Sp j T z

Sw j Sp j T z

Swnew j

i

i i

i

z, according to component

1,2 number of components

0 ( ) ( )

( ) ( ) ( )

( )

w

w

w w

w

= K

î í ì



³

=

Then the unneeded components of the watermark signal Xw( jw) are removed.
These

components correspond to the non-removed components in Sw( jw) . Eq. ( 15 )
is used:

i

i

Xw j Sp j T z

Sp j T z

Xwnew j

i i

i

i

z, according to component

1,2 number of components

( ) ( ) ( )

0 ( ) ( )

( )

w

w w

w

w

= K

î í ì



³

=

22

The factors that will shape the new watermark Xwnew( jw) are found using Eq.
( 18 ):

( )

LBZ HBZ z

z Zt

Xwnew j

T j

F A z

to for each band

1,2

max ( )

( )

=

=

=

w

w

w

K

The square root of the final threshold is divided by the maximum magnitude
component

found in the energy of the new watermark in each critical band. Each one of
these factors is

scaled using the gain A, that varies from 0 to 1, and controls the overall
magnitude of the

watermark signal in relation with the audio signal.

Each one of the components in each critical band k is scaled by the
corresponding factor

using Eq. ( 19 ):

LBZ HBZ z

z Zt

Xfinal j Xwnew j Fz

to for each band

1,2

( ) ( )

=

=

=

w

w w

K

Figure 28 shows the final masking threshold and the watermark signal before
shaping (a) and

after shaping (b). Note that the watermark falls below the threshold of
masking. The factor A

gives control of "how much gain" will have the watermark related with the
masking threshold (A

is a value from 0 to 1).

3.1.7 AUDIO AND WATERMARK SIGNAL COMBINATION

The final output OUT( jw) is the sum of the new audio, Swnew( jw) , and the
final

watermark Xfinal( jw) . This is given by the Eq. ( 20 ):

OUT( jw) = Swnew( jw) + Xfinal( jw)

Figure 29 shows the final masking threshold Tfinal(z), and the power
spectrum of (a) Swnew(jw),

(b) Xfinal(jw), and (c) OUT(jw).

3.1.8 TRANSFORMATION TO THE TIME DOMAIN

The Inverse Fourier Transform is used to convert the frequency domain
information back to

the time domain.

out(t) = IFT{OUT( jw)}

This output frame out(t) is added to the correspondent point at the total
time domain output

output(t). The next frames of audio and watermark signals are taken, and the
process is repeated.

3.2 DATA RECOVERY

The watermarked audio signal is intended to be transmitted through a diverse
number of

channels. In some cases, the channel will introduce noise, convert several
times from digital to

analog and analog to digital, or even use a psychoacoustic auditory model to
process the audio

signal. The watermark bit stream should survive the transmission and be
recoverable.

A very important characteristic is that the developed system does not
require access to the

original audio signal (before watermark) to extract the watermark at the
receiving. The process

of recovery uses the psychoacoustic auditory model, but in this case the
goal is to remove all the

audio components that have less probability of belonging to the watermark
signal. This means

23

that the masking threshold is calculated and the components above it are
removed. The final

signal is the "residual." This residual is then analyzed to find the
possible points where the

watermark is present. If some criterion is applied, the majority of the
false points detected can be

eliminated (i.e. rejecting points too close to fit a watermark).
Synchronization and recovery of

the watermark bit stream are then performed.

3.2.1 MASKING THRESHOLD AND RESIDUAL SIGNAL

The watermarked audio signal after the transmission is symbolized as s2(t).
The process

described in sections 3.1.2 to 3.1.5 is used to calculate the frames sw2(t),
frequency

representation ( ) 2 Sw jw ,and masking threshold T2, respectively. The
residual signal R( jw) is

defined as the signal composed of the components below the masking
threshold. Eq. ( 14 ) can

be changed to:

i

i

Sp j T z

Sw j Sp j T z

R j

i

i i

i

z, according to component

1,2 number of components

0 ( ) ( )

( ) ( ) ( )

( )

2 2

2 2 2

w

w

w w

w

= K

î í ì



£

=

( 68 )

3.2.2 RESIDUAL EQUALIZATION

The spectrum of the residual R( jw) is then shaped to be flat. Eq. ( 18 )
can be modified to

shape all the maximum components of each band to be at equal levels. The
factors are found

using:

( )

LBZ HBZ z

z Zt

R j

Fz

to for each band

1,2

max ( )

1

=

=

=

w

w

K

( 69 )

Each one of the components in each critical band z is scaled by the
corresponding factor Fz using

Eq. ( 19 ):

LBZ HBZ z

z Zt

Rfinal j R j Fz

to for each band

1,2

( ) ( )

=

=

=

w

w w

K

3.2.3 TIME DOMAIN RESIDUAL

The residual is taken back to the time domain using the Inverse Fourier
Transform IFT.

r(t) = IFT{Rfinal( jw)}

The time domain r(t) frame is added to the total time domain residual signal
residual(t) at the

point specified by the frame segmentation step. The next frame is then
processed.

3.2.4 SYNCHRONIZATION WITH WATERMARK HEADER

To be able to synchronize and to have a good de-spreading of the watermark
signal, it is

necessary to have knowledge of the parameters used at the generation of the
watermark signal,

such as f0, Tb, m, H, I, N, {header},{c}, etc.

24

3.2.4.1 header(t) Signal Generat ion

The first step is to generate a header(t) waveform signal using the process
of section 3.1.1,

except that only the {header} sequence is used as the input sequence. This
audio signal will be

used to locate the exact positions of the watermark signals in the
residual(t) signal. Frame

segmentation as explained in section 3.1.2 is also required in order to
analyze the whole

residual(t) signal. The parameters for the frame segmentation are chosen to
have up to two

header(t) signals in each frame. Therefore, BLOCK is equal to twice the
number of samples in

header(t), and OVERLAP is equal to one half the number of samples in
header(t). The resulting

frame taken from residual(t) with BLOCK length is called r(t).

3.2.4.2 header(t) Position Detect ion

Eq. ( 56 ) describes an adaptive high-resolution filter that can be used to
detect the presence

of header(t) in the r(t) frame and therefore, all the occurrences of
header(t) in the residual(t)

audio signal.

2 ( )

* ( )

( )

w

w

w

R j

HEADER j

H j =

Whe ( )

( ) FFT( ( ))

( ) FFT ( )

HEADER j header t

R j r t

=

=

w

w

The denominator of the filter is the smoothed version of 2 R( jw) .
Smoothing is done using Eq.

( 57 ), where w(t) is a Hanning window of width 10%. The output of the
filter applied to

R( jw) is:

2

*

( )

( )

( ) ( )

w

w

w w

R j

HEADER j

DET j = R j

This result is transformed to the time domain to be analyzed.

det(t) = real(IFFT(DET( jw)))

A typical output of the filter, det(t), is shown in Figure 30. The peak
shows the position in

samples where the header(t) signal starts in the frame r(t). This detection
is done for all the

frames in the residual(t) signal, and all the positions of the peaks are
stored for further analysis.

A proposed criterion of analysis is to determine the minimum distance
between peaks to decide

which ones have more probability to represent the start of a watermark
signal.

3.2.5 WATERMARK DE-SPREADING

For each peak position found in the residual(t), a selected frame y(t) with
the same length as

the watermark signal is processed. This process is shown in Figure 31. Using
Eq. ( 35 ):

r(t) = c(t) y(t)

Demodulation is performed using Eq. ( 31 ):

cos(2 )

2

( ) ( ) 0f t

T

g t r t

b

= p

To estimate the bit stream:

25

1,2 total bits in bit stream

( )

( 1)

= K

= ò -

i

r g t dt s

s

iT

i i T ( 70 )

The decision rule, to form a recovered bit stream {d^}, is given by Eq. (
38 ),

1,2 total bits in bit stream

1, if 0

^ 1, if 0

= K

î í ì

- £



=

i

r

r

d

i

i

i

After this decision, the {header} sequence is discarded from the {d^}bit
stream. This produces the

bit stream, { } I w^ .

3.2.6 WATERMARK DE-INTERLEAVING AND DECODING

The de-interleaving process is done using the same matrix used in the
watermark generation

in section 3.1.1 and shown in Figure 14. The bits are written into rows and
read by columns to

accomplish the de-interleaving process. The de-interleaved sequence is
called { } R w^ . The

decoding of the repeat code of value m is done using Eq. ( 53 ):

1,2 total bits in data sequence

1 ^ 0

1 ^ 0

^

1

1

= K

ï ïî

ï ïí

ì

- £



=

å

å

=

=

k

w

w

w m

i

Ri

m

i

Ri

k

The final recovered sequence {w^} is the recovered watermark.

4 SYSTEM PERFORMANCE

4.1 SURVIVAL OVER DIFFERENT CHANNELS

A watermarking system was implemented using a well known mathematical
software

package. The system was composed of two modules: watermark generation and
embedding, and

watermark recovery. The watermark was first generated and embedded in an
audio signal. The

watermarked signal was then tested for recovery of the watermark after
transmission by different

channels, such as sub-band encoding, digital to analog - analog to digital
conversions and radio

transmission.

The music used was a 26 second excerpt of the song "In the Midnight Hour"
(W. Pickett &

S. Cropper) performed by The Commitments. A sampling frequency of 44.1 KHz
was used. Each

of the watermarked audio signals was labeled to reflect the level of the
watermark below the

masking threshold (the A value), i.e. W2, W4, W6 and W8. With these
parameters, a total of 35

watermarks were embedded during the duration of each signal. The four
watermarked music

signals and the original signal were recorded digitally on a compact disc.
The computer was also

equipped with a full duplex sound card with D/A A/D converters. All the
radio systems were

simulated using a multiplex stereo modulator, FM/AM signal generator, and
ordinary consumer

CD player and FM/AM radio receiver. The percentage of correct bits recovered
per watermark

was measured before and after transmission. Two examples are shown in Figure
32 and Figure

33. The percentage of correct bits before transmission is the continuous
line, and the percentage

26

of correct bit after transmission is the dotted line. Also, the offset from
the expected starting

point of each watermark after transmission is measured (in samples), as well
as the total of

watermarks recovered and the average recovery percentage.

4.2 LISTENING TEST

One of the requirements of the watermarking system is to retain the
perceptual quality of the

signal. This is often referred to as "transparency." The transparency of the
watermarking

algorithm was tested using three of the four watermarked audio signals (W2,
W4 and W6) used

in section 4.1. An ABX listening test was used as the testing mechanism. In
an ABX test the

listener can hear selection A (in this case the non-watermarked audio),
selection B (the

watermarked audio) and X (either the watermarked or non-watermarked audio).
The listener is

then asked to decide if selection X is equal to A or B. The number of
correct answers is the basis

to decide if the watermarked audio is perceptually different than the
original audio and would,

therefore, declare the watermarking algorithm as "non-transparent." In the
other case, if the

watermarked audio is perceptually equal to the original audio, the
watermarking algorithm will

be declared as "transparent."

Using the theory explained in Burstein [ 19 ], [ 20 ], different parameters
were selected to

find an appropriate sample size. A criterion of significance a'=0.1 is
selected (also known as

Error Type 1). The Type 2 error risk is assumed b'=0.1. The probability p1
that a listener finds

the right answer by chance is 0.5 in an ABX system. The effect size is
selected as p2=0.7. With

these parameters, the approximated required sample size that meets the
specifications is 37.61

samples. The sample size is selected as n=40. (40 listeners per ABX set).
The critical c (c') is the

minimum number of correct samples which, together with n and p1, can produce
a significance

level a equal to or less than the specified criterion of significance a'.
The calculated c' is 24.55

and can be rounded off to 25. This is the minimum number of correct answers
to accept the

hypothesis that the listener perceives differences between audio A and B.
With c'=25, the

criterion of significance becomes a'=0.78, which is below the required
level. The type 2 error

risk b'=1.11 and does not exceed desired level. The results and their
approximate significance

level are shown in Table 1.

Sample Size Correct Identifications a

W2 40 24 0.14

W4 40 19 0.50

W6 40 19 0.50

Table 1. Listening test results

4.3 DISCUSSION

The survival over different channels showed that after encoding, not all the
watermarks could

be recovered with 100% accuracy. This occurs because of the multiple factors
that affect the

quality of the embedded watermark, such as: the number of audio components
replaced, the gain

of the watermark, and the masking threshold. It is important to note that in
some frames the

watermark information can be very weak, even null. The spread spectrum
technique employed

can partially solve these problems, but if many consecutive frames have no
watermark

information, that specific watermark can not be recovered.

The theoretical position of the watermark and the offset of the actual
watermark represent the

starting position of the {header} of each watermark. This position will not
affect the recovery of

27

the watermark because each watermark is embedded independently of the
others. In the actual

tests three different cases are seen: almost no offset, linearly increasing
offset and varying offset.

When no offset is seen, the original signal and the recorded signal after
transmission where

played at the same speed. In the cases where the offset is linearly, it is
assumed that the speed of

the playback device (in this case an ordinary consumer CD player was
different (slightly slower)

than the recording device. The last case shows the unstable speed variations
of the tape device. If

the speed of the playback device is close enough to the original speed, the
de-spreading can be

successful because the difference in alignment between the watermarked audio
and the despreading

signals (PN sequence, demodulator and {header}) will not greatly affect the
final

result.

Finally, the percentage of correct bits recovered measures quality of the
recovery for each

watermark. Notice that not all the watermarks are recovered (%bits = 0.0),
and not all the

watermarks are recovered in their totality but many of them were recovered
with more than 80%

of the bits. A good bit error detection/correction algorithm or averaging
technique could

substantially improve the recovery of the watermark. A very strong point in
the watermarking

system is the redundancy of watermarks embedded into the audio stream. In
this case, each

watermark lasts approximately 600 ms. Even if just a few watermarks are
recovered, the goal of

transmitting the watermark information within the audio signal and
recovering it afterwards is

accomplished.

The listening test showed that the watermark at -2dB below the masking
threshold (W2) is

the most likely to be heard, but it can not be ensured that people actually
noticed the difference.

For all the other watermarked signals, the results show that the process is
"transparent."

5 CONCLUSIONS

The proposed digital watermarking method for audio signals is based on a
psychoacoustic

auditory model to shape an audio watermark signal that is generated using
spread spectrum

techniques. The method retains the perceptual quality of the audio signal,
while being resistant to

diverse removal attacks, either intentional or unintentional. The recovery
of the watermark is

accomplished without knowledge of the original audio signal. The only
information used

includes the watermarked audio signal, and the parameters used for the
watermark generation.

The psychoacoustic auditory model retrieves the necessary information about
the masking

threshold of the input audio signal. This model is a good approach that can
be used for several

applications such: perceptual coding, masking analysis, or watermark
embedding. The spread

spectrum theory describes two important Direct Sequence techniques, but the
employed

technique is Coded Direct-Sequence Spread Binary Phase-Shift-Keying (coded
DS/BPSK).

Because the normal literature about this topic is reserved for communication
theory, some

assumptions were made to use the theory in an audio bandwidth environment.
Specifically in this

case, the audio information was considered the "noise" or "jammer" signal
that interferes with

the watermark.

Future research could be performed in different aspects of this proposed
algorithm such as:

- System performance with different types of music.

- Experimenting with different spread spectrum encoding parameters.

- Changes in the playback speed of the signal.

- Crosstalk interference.

- Multiple watermark embedding.

28

- Use of techniques to enhance recovery of the watermark (i.e., bit error
detection/ correction,

averaging, etc).

- Real - time implementation.

- Investigate different signal schemes for the generation of the PN
sequence.

6 ACKNOWLEDGMENT

The author wishes to thank Professors Ken Pohlmann and Will Pirkle from the
Music

Engineering program at University of Miami for their valuable advises and
feedback. Also to the

Music Engineer Alex Souppa for his help as technical editor and english
corrector of the author's

master thesis.

7 REFERENCES

[ 1 ] E. Zwicker and U. T. Zwicker, "Audio Engineering and Psychoacoustics:
Matching Signals

to the Final Receiver, the Human Auditory System," J. Audio Eng. Soc., vol.
39, pp. 115 -126

(1991 March)

[ 2 ] T. Sporer and K. Brandenburg, "Constraints of Filter Banks Used for
Perceptual

Measurement," J. Audio Eng. Soc., vol. 43, pp. 107 - 115 (1995 March)

[ 3 ] J. Mourjopoulos and D. Tsoukalas, "Neural Network Mapping to
Subjective Spectra of

Music Sounds," J. Audio Eng. Soc., vol. 40, pp. 253 - 259 (1992 April)

[ 4 ] J. D. Johnston, "Transform Coding of Audio Signals Using Perceptual
Noise Criteria,"

IEEE Journal on Selected Areas in Communications, vol. 6, pp. 314 - 323
(1988 Feb.)

[ 5 ] M. K. Simon, J. K Omura, R A. Scholtz and B. K. Levitt, Spread
Spectrum

Communications Handbook (McGraw-Hill, New York, 1994)

[ 6 ] R. L. Pickholtz, D. L. Schilling, and L. B. Milstein, "Theory of
Spread-Spectrum

Communications - A Tutorial," IEEE Transactions on Communications, vol.
COM-30, pp. 855

- 884 (1982 May)

[ 7 ] C. S. Lindquist, Adaptive & Digital Signal Processing with Digital
Filtering Applications

(Steward & Sons, Miami, 1989)

[ 8 ] L. R. Rabiner, and R. W. Schafer, Digital Processing of Speech Signals
(Prentice Hall, New

Jersey, 1978)

[ 9 ] E. Zwicker, and h. Fastl, Psychoacoustics Facts and Models
(Springer-Verlag, Berlin, 1990)

[ 10 ] D. L. Nicholson, Spread Spectrum Signal Design. LPE & AJ Systems
(Computer Science

Press, Rockville, Maryland, 1988)

[ 11 ]C. Neubauer and J. Herre, "Digital Watermarking and Its Influence on
Audio Quality,"

presented at the 105th Convention of the Audio Engineering Society, J. Audio
Eng. Soc.

(Abstracts), vol. 46, pp. 1041 (1998 November), preprint 4823.

[ 12 ] J. G. Roederer, The Physics and Psychophysics of Music
(Springer-Verlag, New York,

1995)

[ 13 ] J. G. Beerends and J. A. Stemerdink, "A Perceptual Speech-Quality
Measure Based on a

Psychoacoustic Sound Representation," J. Audio Eng. Soc., vol. 42, pp. 115 -
123 (1994 March)

[ 14 ] J. G. Beerends and J. A. Stemerdink, "A Perceptual Audio Quality
Measure Based on a

Psychoacoustic Sound Representation," J. Audio Eng. Soc., vol. 40, pp. 963 -
978 (1992

December)

[ 15 ] C. Colomes, M. Lever, J. B. Rault, Y. F. Dehery and G. Faucon, "A
Perceptual Model

Applied to Audio Bit-Rate Reduction," J. Audio Eng. Soc., vol. 43, pp. 233 -
239 (1995 April)

29

[ 16 ] T. Sporer, G. Gbur, J. Herre and R. Kapust, "Evaluating a Measurement
System," J. Audio

Eng. Soc., vol. 43, pp. 353 - 362 (1995 May)

[ 17 ] M. R. Schroeder, B. S. Atal and J. L. Hall, "Optimizing Digital
Speech Coders by

Exploiting Masking Properties of the Human Ear," J. Acoust. Soc. Am., vol.
66, pp. 1647 - 1652

(1979 Dec.)

[ 18 ] B. Paillard, P. Mabilleau, S. Morissette and J. Soumagne, "PERCEVAL:
Perceptual

Evaluation of the Quality of Audio Signals," J. Audio Eng. Soc., vol. 40,
pp. 21 - 31 (1992

Jan./Feb.)

[ 19 ] H. Burstein, "By the Numbers," Audio, vol. 74, pp. 43 - 48 (1990
Feb.)

[ 20 ] H. Burstein, "Approximation Formulas for Error Risk and Sample Size
in ABX Testing,"

J. Audio Eng. Soc., vol. 36, pp. 879 - 883 (1988 Nov.)

[ 21 ] S. Haykin, Communication Systems 3rd ed. (Wiley, New York, 1994)

[ 22 ] R. L. Shrader, Electronic Communication 5th ed. (McGraw Hill, New
York, 1985)

[ 23 ] L. Boney, A. H. Tewfik and K. N. Hamdy, "Digital Watermarks for Audio
Signals," IEEE

Int.Conf. on Multimedia Computing and Systems, Hiroshima, Japan (June 1996)

[ 24 ] I. J. Cox, "Spread Spectrum Watermark for Embedded Signalling",
United States Patent

5,848,155 (1998 Dec)

30

FFT Power Spectrum Energy per

Critical Band

Spread Masking

Across

Critical Bands

Masking

Threshold

Estimate

IFFT Noise Shaping

s(t) S(jw) Sp(jw)

Spz(z)

B(z)

Sm(z)

T(z)

N(jw)

out(t) OUT(jw)

Figure 1. Psychoacoustic auditory model

0 1 2 4 6 8 10 12 14 16

Frequency [kHz] Frequency [kHz]

80

60

40

20

0

80

60

40

20

0

Excitation level [dB]

Excitation level [dB]

f =8kHz c 1 4

0.02 0.05 0.1 0.2 0.5 1 2 5 10 20

f =0.07 c 0.25 1 4kHz

(a) (b)

Figure 2. Masking curves in (a) linear and (b) logarithmic frequency scale
[ 1 ]

0 2 4 6 8 10 12 14 16 18 20 22 24

critical band rate z [Barks]

60

40

20

0

Excitation level [dB]

Figure 3. Excitation level versus critical band rate for narrow band noises
with various center frequencies [ 1 ]

31

Figure 4. Model of the spreading function, B(z), using Eq. ( 5 )

Transmitter Receiver

Jammer

PG=

Wss

Rb

J

S

=Jammer to Signal power ratio

E

N

b

j

PG

J/S

=

J=Jammer Power

Wss = Bandwidth

Rb = Bit Rate (bits/sec)

S = Power

Figure 5. Basic spread spectrum communications system

2

Tb

Frequency [Hz] Magnitude 2

Tb

2 = N*

Tc

Frequency [Hz]

Magnitude

Figure 6. Spectrum of signal BPSK Figure 7. Spectrum of signal BPSK after

spreading

32

PN

Generator

BPSK

Modulator

d(t) x(t)

c(t)

Figure 8. DS/BPSK modulation

PN

Generator

BPSK

Modulator

d(t) x(t)

c(t)

s(t)

Figure 9. DS/BPSK modified

PN

Generator

PN

Generator

BPSK

Modulator

d(t) x(t)

c(t)

c(t)

s(t)

J(t)

y(t)

r r(t)

cos( )

2

0t

Tb

w

( )dt Tb

0 ò ·

Transmitter

Receiver

Transmission

Channel

Figure 10. Uncoded DS/BPSK

33

Tb

Tc

Ts

d(t)

c(t)

a(t)

c(t)d(t)

c(t)a(t)

Figure 11. Coded and uncoded signals before

spreading

Figure 12. Coded and uncoded signals after

spreading

34

PN

Generator

PN

Generator

c(t)

c(t)

BPSK

MODULATOR

INTERLEAVER

REPEAT

CODER

DEDECODER

INTERLEAVER

d

Tb

Tb

m

m

T = s T

m

b

di

I H

I H f0

s(t)

J(t)

ri

Ts

d^

Transmission

x(t) Channel

y(t)

Figure 13. Repeat code DS/BPSK system

X1 X16 X31 X46 X61

X2 X17 X32 X47 X62

X3 X18 X33 X48 X63

X4 X19 X34 X49 X64

X5 X20 X35 X50 X65

X6 X21 X36 X51 X66

X7 X22 X37 X52 X67

X8 X23 X38 X53 X68

X9 X24 X39 X54 X69

X10 X25 X40 X55 X70

X11 X26 X41 X56 X71

X12 X27 X42 X57 X72

X13 X28 X43 X58 X73

X14 X29 X44 X59 X74

X15 X30 X45 X60 X75

Figure 14. Interleaver matrix with I=5 and H=15

35

s(n) r(n) R(m) C(m) P(m) p(n)

n(n)

+

+

FFT H(m) G(m) IFFT

Ideal

Filter

Post

Processing

Filter

Figure 15. FFT filter assuming additive signal and noise

WATERMARK

GENERATION

Coded DS/BPSK

PSYCHOACOUSTIC

AUDITORY

MODEL

WATERMARK

SHAPING

AND

EMBEDDING

10110...1001

WATERMARK

(bit stream)

AUDIO

WATERMARKED

AUDIO

T(z) TRANSMISSION

CHANNEL

PARAMETERS

Figure 16 Proposed system (watermark generation and embedding)

T(z) r(t)

AUDITORY

MODEL

DE-SPREADING

AND

RECOVERY

ADAPTIVE

HIGH

RESOLUTION

DETECTION

RESIDUAL

GENERATION

HEADER

GENERATION

10110...1001

TRANSMISSION

CHANNEL

RECOVERED

WATERMARK

PARAMETERS

Figure 17 Proposed System (Data recovery)

36

PN

Generator

c(t)

BPSK

MODULATOR

REPEAT INTERLEAVER

CODER

{w}

Tw

m

Tb=

T

m

w

{wR}

I H f0

HEADER s(t)

INJECTION

{wI}

Tb

{header}

{d}={header}+{w}I

x(t)

Figure 18. Watermark generation system

1 1 1 -1 1

1 1 -1 -1 1

1 -1 -1 -1 -1

1 -1 -1 1 -1

1 -1 1 1 -1

1 -1 1 1 -1

-1 -1 1 1 -1

-1 -1 1 1 -1

-1 1 1 1 1

1 1 1 1 1

Figure 19. Interleaver matrix

FS

2

FS

2

A

Rc

2*Rc

Figure 20. Baseband System Parameters

37

FS

2

FS

2

A

2*Rc

Rc Rc

A

2

-f0 f0

Figure 21. Passband System Parameters (anti-aliasing)

FS

2

FS

2

A

LF+Rc HF+Rc

A

2

-f0 f0

Figure 22. Passband System with Frequency Limits LF and HF

Figure 23 Time domain signals: data bit stream, d(t); PN sequence, c(t);
BPSK modulator, sin(t); and

watermark audio signal, x(t)

38

Audio Signal

Watermark signal

LENGTH

FRAME

Figure 24. Frame segmentation and watermark redundancy

Figure 25. (a) Audio signal s(t) and window signal w(t), (b) windowed signal
sw(t), (c) magnitude of

frequency representation Sw(jw), and (d) power spectrum Sp(jw) and energy
per critical band Spz(z)

39

Figure 26. (a) Energy per critical band Spz(z), (b) spreading function B(z),
and (c) Spread energy per

critical band Sm(z)

Figure 27. (a) raw masking threshold Traw(z), and (b) normalized masking
threshold Tnorm(z)

40

Figure 28. (a) Xwnew(z) before shaping, (b) after shaping with A = 0.4

Figure 29. Final masking threshold Tfinal(z), and the power spectrum of (a)
Swnew(jw), (b) Xfinal(jw),

and (c) OUT(jw).

41

Figure 30. Detection peak in det(t)

PN

Generator

c(t)

{w}

Tw

m

{wR}

I H

r(t) HEADER

REMOVAL

{wI}

Td

{header}

y(t) DEINTERLEAVER

DECODER

g(t) {d^} ^ ^

Figure 31. Watermark recovery system

Figure 32 MPEG layer 3 system performance

42

Figure 33 FM stereo (left channel) system performance


  #5   Report Post  
Posted to rec.audio.opinion
Robert Morein
 
Posts: n/a
Default It's amazing what you can find when you look.


wrote in message
ink.net...
Oooh look at all those lines.


So now you're a newsgroup spammer.

Very impressive.




  #7   Report Post  
Posted to rec.audio.opinion
Clyde Slick
 
Posts: n/a
Default It's amazing what you can find when you look.


wrote in message
ink.net...
Oooh look at all those lines.


Mi

c

key

,

yo

u ar

a

fuc

king

mo
r

o

n
..



  #11   Report Post  
Posted to rec.audio.opinion
George M. Middius
 
Posts: n/a
Default It's amazing what you can find when you look.



dave weil said:

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


[sigh]

dave, we've covered this before. The real purpose of the blinding rituals is
to brainwash Normals into believing that everything sounds the same. Since
duh-Mikey already believes everything sounds the same, he doesn't need the
brainwashing. So of course there's no point for him to undergo the rituals.





  #14   Report Post  
Posted to rec.audio.opinion
Ruud Broens
 
Posts: n/a
Default It's amazing what you can find when you look.


"Clyde Slick" wrote in message
...
:
: wrote in message
: ink.net...
: Oooh look at all those lines.
:
:
: Mi
:
: c
:
: key
:
: ,
:
: yo
:
: u ar
:
: a
:
: fuc
:
: king
:
: mo
: r
:
: o
:
: n
: .
:
:
I can see i have popularized the wrap around technique
of debating where will it all go to /come to / doobedoo ;-) ?

the wrapper


  #17   Report Post  
Posted to rec.audio.opinion
 
Posts: n/a
Default It's amazing what you can find when you look.


"paul packer" wrote in message
...
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
groups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.


Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake.


Then I guess you will have to go unsatisfied.

When Istared posting here over 10 years ago, ABX was already accepted
science. I had no idea that was a controversey for anybody other than a few
nutcases I'd met. I didn't realize there was an entire cult built around
denying reality. The audio version of the flat earth folks.

That is, one can understand Arny defending it, but in
fact he spends less time doing so than you. One would almost think he
were paying you, as you suggest George is paying me.


People keep denying reality, I keep reminding them reality is real, their
fantasies about sighted listening as a reliable way to judge subtle
differences is not.

As long as it pleasers me to do so, when people lie or misrepresent facts,
I'll make sure I set the record straight. That applies to my own errors as
well.



  #18   Report Post  
Posted to rec.audio.opinion
Robert Morein
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 00:55:39 GMT, wrote:


"paul packer" wrote in message
...
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
egroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.


Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake. That is, one can understand Arny defending it, but in
fact he spends less time doing so than you. One would almost think he
were paying you, as you suggest George is paying me.


yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
  #19   Report Post  
Posted to rec.audio.opinion
Robert Morein
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 01:14:45 GMT, wrote:


"paul packer" wrote in message
...
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
egroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.


Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake.


Then I guess you will have to go unsatisfied.

When Istared posting here over 10 years ago, ABX was already accepted
science. I had no idea that was a controversey for anybody other than a few
nutcases I'd met. I didn't realize there was an entire cult built around
denying reality. The audio version of the flat earth folks.

That is, one can understand Arny defending it, but in
fact he spends less time doing so than you. One would almost think he
were paying you, as you suggest George is paying me.


People keep denying reality, I keep reminding them reality is real, their
fantasies about sighted listening as a reliable way to judge subtle
differences is not.

As long as it pleasers me to do so, when people lie or misrepresent facts,
I'll make sure I set the record straight. That applies to my own errors as
well.


Yes I love you Mr KNOB
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
  #20   Report Post  
Posted to rec.audio.opinion
Robert Morein
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 00:54:44 GMT, wrote:


"dave weil" wrote in message
.. .
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
egroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.

I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


What is the relevance?
None.

What I've used to decide on my own audio gear has no bearing at all on the
efficacy of ABX.


yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes


  #21   Report Post  
Posted to rec.audio.opinion
Robert Morein
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 00:55:39 GMT, wrote:


"paul packer" wrote in message
...
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
egroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.


Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake. That is, one can understand Arny defending it, but in
fact he spends less time doing so than you. One would almost think he
were paying you, as you suggest George is paying me.



yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes yes
  #22   Report Post  
Posted to rec.audio.opinion
dave weil
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 00:54:44 GMT, wrote:


"dave weil" wrote in message
.. .
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
egroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.

I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


What is the relevance?
None.


You're kidding, right? It's certainly relevant if you yourself don't
use it. If it's so efficacious, why not use it yourself?

What I've used to decide on my own audio gear has no bearing at all on the
efficacy of ABX.


It has EVERYTHING to do with castigating those who DON'T use it and
saying that it's the only way to get to "THE TRVTH".

I think everyone can now see that you don't have the confidence in the
very thing that you promote.

BTW, I don't deny that it's one way to compare gear, just not the only
"true" way and not even necessarily the best way to compare gear,
although it might not be the worst either. It's certainly better than
buying stuff on the basis of reading a tech sheet.
  #23   Report Post  
Posted to rec.audio.opinion
dave weil
 
Posts: n/a
Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 01:14:45 GMT, in rec.audio.opinion you wrote:

Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake.


Then I guess you will have to go unsatisfied.

When Istared posting here over 10 years ago, ABX was already accepted
science. I had no idea that was a controversey for anybody other than a few
nutcases I'd met. I didn't realize there was an entire cult built around
denying reality. The audio version of the flat earth folks.


So, 10 years later, you haven't bothered to even use ABX to make a
single audio purchase. Amazing that you spend so much energy exhorting
others to do just that.

You buy audio gear just like 99.9% of the universe does - you audition
it, you read reviews, you listen to others, you might even listen to
it against other gear in a showroom. You even read the tech sheets.

Hey, this is just like Arnold does. Even the Grand Poohbah doesn't use
it.

Welcome to the 21st Century.

  #24   Report Post  
Posted to rec.audio.opinion
George M. Middius
 
Posts: n/a
Default It's no accident dinosaurs are extinct



dave weil said:

I don't deny that [aBxism is] one way to compare gear, just not the only
"true" way and not even necessarily the best way to compare gear,
although it might not be the worst either. It's certainly better than
buying stuff on the basis of reading a tech sheet.


I can't agree with that. To do such a "test", you have to have both items
in your possession, as well as the requisite switchbox. That's time and
money you have to invest. Since the purported objective of the "test" is to
undermine the rationale for spending extra money, it's circular at best.

It's also doubtful whether Joe Audiophile can simply sit down and do a
"test" and reach a meaningful decision for the intended purpose of his
purchase, which is listening to music for pleasure. If you take the
pleasure part out of the equation and try to treat the exercise as
"research", how do you translate the results into a meaningful conclusion
for the real context?

It's a fantasy to pretend that human beings can turn themselves into robots
just to choose one box over another. We have emotions and feelings and
moods. Our response to music varies according to our emotional state. On a
given day, you might be more receptive to one aspect of a recording because
of some connotation of a particular sound. Such subtleties are completely
masked by the roboticism of the "tests".

In the end, if you use aBxism rituals to choose your gear, you have no
assurance you've made the best choice because the "test" is artificial. The
'borgs themselves tacitly admit this point -- none of Them has EVER used a
"test" to guide a single purchase for personal use. Never. Not one.





  #25   Report Post  
Posted to rec.audio.opinion
dave weil
 
Posts: n/a
Default It's no accident dinosaurs are extinct

On Sun, 20 Nov 2005 09:21:59 -0500, George M. Middius cmndr
[underscore] george [at] comcast [dot] net wrote:



dave weil said:

I don't deny that [aBxism is] one way to compare gear, just not the only
"true" way and not even necessarily the best way to compare gear,
although it might not be the worst either. It's certainly better than
buying stuff on the basis of reading a tech sheet.


I can't agree with that. To do such a "test", you have to have both items
in your possession, as well as the requisite switchbox. That's time and
money you have to invest. Since the purported objective of the "test" is to
undermine the rationale for spending extra money, it's circular at best.

It's also doubtful whether Joe Audiophile can simply sit down and do a
"test" and reach a meaningful decision for the intended purpose of his
purchase, which is listening to music for pleasure. If you take the
pleasure part out of the equation and try to treat the exercise as
"research", how do you translate the results into a meaningful conclusion
for the real context?

It's a fantasy to pretend that human beings can turn themselves into robots
just to choose one box over another. We have emotions and feelings and
moods. Our response to music varies according to our emotional state. On a
given day, you might be more receptive to one aspect of a recording because
of some connotation of a particular sound. Such subtleties are completely
masked by the roboticism of the "tests".


It's just another tool. If one wishes to invest time and/or money in
it, there's nothing wrong with using it to augment the buying process.
The folly is to rely on it exclusively.

The worst way to buy gear (IMO) is to read a tech sheet and buy solely
on that basis. Therefore, ABX can't be the worst way. At least you're
listening to the darn stuff. I think you are arguing that
ABX could mislead you. That's why you don't use it exclusively or
demand that it's the only valid way to perform a listening test.

In the end, if you use aBxism rituals to choose your gear, you have no
assurance you've made the best choice because the "test" is artificial. The
'borgs themselves tacitly admit this point -- none of Them has EVER used a
"test" to guide a single purchase for personal use. Never. Not one.


Of course it's artificial. So is a sighted listening test for that
matter because you're listening analytically, and that imposes an
artificiality not found in normal "listening for pleasure". Is it more
natural than ABX? Well, yes. But that doesn't disqualify ABX (or DBT
to speak more generally) for those who want to take the time (or the
money) to try a different testing paradigm. Now, extending the
concept to PCABX, I think that are far bigger flaws in that paradigm,
such as sample size, imposition of a PC, setup, etc. that I think
keeps it from being anything more than a simple parlor game for most
consumers.


  #26   Report Post  
Posted to rec.audio.opinion
 
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Default It's amazing what you can find when you look.

I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


I'll interject a comment here. I've never run an ABX test, although I have
participated in some that were run by others. I have, however, run several
single blind tests, and it can be safely stated that failure to pass a SBT
insures that you will not pass a DBT either.

I ran a simple A-B test of a CD v. a CDR copy about 3 years ago. I was
unable to tell the difference. I also ran a test of bi-wiring, using 3
different gauges of wire in lengths of 33 ft. This test was run using a
well known speaker whose maker recommended bi-wiring. No difference was
found until the wire size got down to 24Ga.

Norm Strong


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Robert Morein
 
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Default It's amazing what you can find when you look.


wrote in message
. ..
I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


I'll interject a comment here. I've never run an ABX test, although I
have participated in some that were run by others. I have, however, run
several single blind tests, and it can be safely stated that failure to
pass a SBT insures that you will not pass a DBT either.

I ran a simple A-B test of a CD v. a CDR copy about 3 years ago. I was
unable to tell the difference. I also ran a test of bi-wiring, using 3
different gauges of wire in lengths of 33 ft. This test was run using a
well known speaker whose maker recommended bi-wiring. No difference was
found until the wire size got down to 24Ga.

Norm Strong

Also, I think it's highly probable that if one cannot distinguish in a
sighted test, there will be no distinction in a blind test.


  #28   Report Post  
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Clyde Slick
 
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Default It's amazing what you can find when you look.


wrote in message
. ..
I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.


When was the last time YOU used it for such a purpose?


I'll interject a comment here. I've never run an ABX test, although I
have participated in some that were run by others. I have, however, run
several single blind tests, and it can be safely stated that failure to
pass a SBT insures that you will not pass a DBT either.

I ran a simple A-B test of a CD v. a CDR copy about 3 years ago. I was
unable to tell the difference. I also ran a test of bi-wiring, using 3
different gauges of wire in lengths of 33 ft. This test was run using a
well known speaker whose maker recommended bi-wiring. No difference was
found until the wire size got down to 24Ga.


How's that $25 surround sound speaker system you just bought?
I'm sure your purchasing decision was based upon proper and rigorous DBT.


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"dave weil" wrote in message
...
On Sun, 20 Nov 2005 01:14:45 GMT, in rec.audio.opinion you wrote:

Er...no, actually. Whatever the answer was, it didn't satisfy my
curiousity as to why anbody would invest so much time and energy into
defending a product in which he had no financial or, presumably,
emotional stake.


Then I guess you will have to go unsatisfied.

When Istared posting here over 10 years ago, ABX was already accepted
science. I had no idea that was a controversey for anybody other than a
few
nutcases I'd met. I didn't realize there was an entire cult built around
denying reality. The audio version of the flat earth folks.


So, 10 years later, you haven't bothered to even use ABX to make a
single audio purchase. Amazing that you spend so much energy exhorting
others to do just that.

I only suggest it when there's a question of sublte differences. If I ever
that question, I wouldn't hesitate to use ABX to resolve it.




You buy audio gear just like 99.9% of the universe does - you audition
it, you read reviews, you listen to others, you might even listen to
it against other gear in a showroom. You even read the tech sheets.

Hey, this is just like Arnold does. Even the Grand Poohbah doesn't use
it.

Welcome to the 21st Century.

I don't care if you or anybody uses ABX. It has an appropiate use and it is
one of the best ways to resolve questions of subtle differences. Being one
of the people who realizes that much of the stuff alleged to sound better
actually doesn't sound any different, there's not much reason for me to use
such a method. There seem to plenty of people who don't realize that a lot
of stuff sounds just like other stuff. For them ABX is a solution.



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Default It's amazing what you can find when you look.


"dave weil" wrote in message
...
On Sun, 20 Nov 2005 00:54:44 GMT, wrote:


"dave weil" wrote in message
. ..
On Sat, 19 Nov 2005 21:14:55 GMT, wrote:


wrote in message
legroups.com...

wrote:
Oooh look at all those lines.

(snip boring stuff--that's all of it)

Mike, you still haven't answered my question about what you have to
gain from defending ABX with such passion and verbosity. Considering
that you must spend several hours a day doing so, I think this is
something we'd all like to know.

Already answered, the last time you asked.

I like the truth, I try to defend the truth every chance I get.
I also like poking holes in the idiotic arguments that people who try to
discredit ABX so often use.

ABX is a valid way to compare gear for subtle differences. It's not a
matter of opinion, it is demonstrable fact.

When was the last time YOU used it for such a purpose?


What is the relevance?
None.


You're kidding, right? It's certainly relevant if you yourself don't
use it. If it's so efficacious, why not use it yourself?

I have no need, I'm not in doubt about subtle differnces. When I am I wil
use it.

What I've used to decide on my own audio gear has no bearing at all on the
efficacy of ABX.


It has EVERYTHING to do with castigating those who DON'T use it and
saying that it's the only way to get to "THE TRVTH".


I have never said any such thing. I've said that it is a way that can
answer the question of differences between components when all reason says
there should be none. Another form of bias controlled comparison would also
be satisfactory.

I think everyone can now see that you don't have the confidence in the
very thing that you promote.

I think everyone can see that you are not above stretching the truth in your
attempts to deny ABX as a relaible tool for determining difference.


BTW, I don't deny that it's one way to compare gear, just not the only
"true" way and not even necessarily the best way to compare gear,
although it might not be the worst either.


One thing that is CERTAIN is that it works for determining subtle
difference, and sighted listening is useless except for gross differences.

It's certainly better than
buying stuff on the basis of reading a tech sheet.


Since competently desingned and built audio equipment has no "sound" of it's
own, even a tech sheet should be unneccessary other than for power output
and a couple other minor deteails.





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paul packer
 
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Default It's amazing what you can find when you look.

On Sun, 20 Nov 2005 20:58:07 GMT, wrote:

There seem to plenty of people who don't realize that a lot
of stuff sounds just like other stuff.


And who are these people? I certainly realize that one JVC integrated
sounds pretty much like another JVC integrated, and pretty much like
an Akai integrated as well. It just happends that I don't like the
sound of any of them.

For them ABX is a solution.


Not as good as suicide though.

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Default It's no accident dinosaurs are extinct


"George M. Middius" cmndr [underscore] george [at] comcast [dot] net wrote
in message ...


dave weil said:

I don't deny that [aBxism is] one way to compare gear, just not the only
"true" way and not even necessarily the best way to compare gear,
although it might not be the worst either. It's certainly better than
buying stuff on the basis of reading a tech sheet.


I can't agree with that. To do such a "test", you have to have both items
in your possession, as well as the requisite switchbox.


No you don't. Cable swaps are another way.

That's time and
money you have to invest. Since the purported objective of the "test" is
to
undermine the rationale for spending extra money, it's circular at best.


That's not the rationale, that's simnply turned out to be a side benefit.
Knowing that the identical sound quality can be had for less than what some
people wish you to believe was not and is not the sole reason to use ABX.
The main reason is and always has been to determine if difference exists.


It's also doubtful whether Joe Audiophile can simply sit down and do a
"test" and reach a meaningful decision for the intended purpose of his
purchase, which is listening to music for pleasure. If you take the
pleasure part out of the equation and try to treat the exercise as
"research", how do you translate the results into a meaningful conclusion
for the real context?



Unfortunately, there is no evidence to back up that assertion, nor is there
any requirement that people listen to anything they don't want to, and for
as long as they want to, so long as they can switch between level matched
devices. Part of the anger from those who endorse ABX is due to teh fact
that you and the otehr people who argue against it, feel the need to lie and
distort what happens in an ABX test.

It's a fantasy to pretend that human beings can turn themselves into
robots
just to choose one box over another.


It's fantasy to believe that anything meaningful can be determined by a
sighted comparison of non level matched gear.

We have emotions and feelings and
moods. Our response to music varies according to our emotional state. On a
given day, you might be more receptive to one aspect of a recording
because
of some connotation of a particular sound. Such subtleties are completely
masked by the roboticism of the "tests".

And your tests that show this to be true are where?

In the end, if you use aBxism rituals to choose your gear, you have no
assurance you've made the best choice because the "test" is artificial.


And your research that proves this tio be true is where?

The
'borgs themselves tacitly admit this point -- none of Them has EVER used a
"test" to guide a single purchase for personal use. Never. Not one.


And you still don't understand why?



  #33   Report Post  
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Ruud Broens
 
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Default It's no accident dinosaurs are extinct


"George M. Middius" cmndr [underscore] george [at] comcast [dot] net wrote in
message ...
:
:
: dave weil said:
:
: I don't deny that [aBxism is] one way to compare gear, just not the only
: "true" way and not even necessarily the best way to compare gear,
: although it might not be the worst either. It's certainly better than
: buying stuff on the basis of reading a tech sheet.
:
: I can't agree with that. To do such a "test", you have to have both items
: in your possession, as well as the requisite switchbox. That's time and
: money you have to invest. Since the purported objective of the "test" is to
: undermine the rationale for spending extra money, it's circular at best.
:
: It's also doubtful whether Joe Audiophile can simply sit down and do a
: "test" and reach a meaningful decision for the intended purpose of his
: purchase, which is listening to music for pleasure. If you take the
: pleasure part out of the equation and try to treat the exercise as
: "research", how do you translate the results into a meaningful conclusion
: for the real context?
:
: It's a fantasy to pretend that human beings can turn themselves into robots
: just to choose one box over another. We have emotions and feelings and
: moods. Our response to music varies according to our emotional state. On a
: given day, you might be more receptive to one aspect of a recording because
: of some connotation of a particular sound. Such subtleties are completely
: masked by the roboticism of the "tests".
:
: In the end, if you use aBxism rituals to choose your gear, you have no
: assurance you've made the best choice because the "test" is artificial. The
: 'borgs themselves tacitly admit this point -- none of Them has EVER used a
: "test" to guide a single purchase for personal use. Never. Not one.
:
:

clearly formulated , well argumented nice post George :-)

most of the audio testing protocols i've seen, use a system of rating various
DUT's on some scale, that is, implied is that "the participant is in a position
to
judge various aspects of the DUT".
ABX has an all together other implication: "we doubt you are even able to
hear any differences between two DUT's."
being judge or being suspect err, your votes, please ;-)

Rudy


  #34   Report Post  
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George M. Middius
 
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Default It's amazing what you can find when you look.



paul packer said to duh-Mikey:

For them ABX is a solution.


Not as good as suicide though.


Now you're getting into the spirit.




  #35   Report Post  
Posted to rec.audio.opinion
George Middius
 
Posts: n/a
Default It's no accident dinosaurs are extinct




duh-Mikey demonstrates, yet again, how difficult it is for him to pass for a
regular person.
It's also doubtful whether Joe Audiophile can simply sit down and do a
"test" and reach a meaningful decision for the intended purpose of his
purchase, which is listening to music for pleasure. If you take the
pleasure part out of the equation and try to treat the exercise as
"research", how do you translate the results into a meaningful conclusion
for the real context?


Unfortunately, there is no evidence to back up that assertion


Speaking of evidence, a Normal could easily be swayed into believing you're a
freako-geeko experiment in AI enslaved to a religious proselytizer.

We have emotions and feelings and
moods. Our response to music varies according to our emotional state. On a
given day, you might be more receptive to one aspect of a recording
because of some connotation of a particular sound. Such subtleties
are completely masked by the roboticism of the "tests".


And your tests that show this to be true are where?


I'm sorry, Mickey. I should have noted I was speaking on behalf of human beings
and not robots. You should consider yourself excluded from all generalizations
about how human beings use their stereos.



..
..
..



  #36   Report Post  
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"paul packer" wrote in message
...
On Sun, 20 Nov 2005 20:58:07 GMT, wrote:

There seem to plenty of people who don't realize that a lot
of stuff sounds just like other stuff.


And who are these people? I certainly realize that one JVC integrated
sounds pretty much like another JVC integrated, and pretty much like
an Akai integrated as well. It just happends that I don't like the
sound of any of them.

For them ABX is a solution.


Not as good as suicide though.



  #37   Report Post  
Posted to rec.audio.opinion
 
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Default It's amazing what you can find when you look.


"paul packer" wrote in message
...
On Sun, 20 Nov 2005 20:58:07 GMT, wrote:

There seem to plenty of people who don't realize that a lot
of stuff sounds just like other stuff.


And who are these people? I certainly realize that one JVC integrated
sounds pretty much like another JVC integrated, and pretty much like
an Akai integrated as well. It just happends that I don't like the
sound of any of them.

And if they sound like a Yamaha integrated then they probably sound just
like the expensive Pass monoblocks that Steve Zipser could not tell a
difference between.

The problem is that most claims of difference have no basis in fact. If
there were freal evidence to suggest that there's some difference between
most solid state components then it would be a major selling point.
However, since nobody is stepping forward with their DBT results to show
those differences, it seems fair to conclude that such differences are very
rare.

For them ABX is a solution.


Not as good as suicide though.

Then don't use ABX, use some other form of bias controlled, level matched,
blind listening. Rely on your ears, but only on your ears.


  #38   Report Post  
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"George M. Middius" cmndr [underscore] george [at] comcast [dot] net wrote
in message ...


paul packer said to duh-Mikey:

For them ABX is a solution.


Not as good as suicide though.


To which Ingnorant George replied:

Now you're getting into the spirit.


Give us a demonstration.


  #39   Report Post  
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Arny Krueger
 
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Default It's amazing what you can find when you look.

wrote in message
nk.net
"George M. Middius" cmndr [underscore] george [at]
comcast [dot] net wrote in message
...


paul packer said to duh-Mikey:

For them ABX is a solution.

Not as good as suicide though.


To which Ingnorant George replied:

Now you're getting into the spirit.


Give us a demonstration.


Futile. Neither Satan nor demons can die.


  #40   Report Post  
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Arny Krueger
 
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Default It's amazing what you can find when you look.

"paul packer" wrote in message

On Sun, 20 Nov 2005 20:58:07 GMT,
wrote:

There seem to plenty of people who don't realize that a
lot of stuff sounds just like other stuff.


And who are these people? I certainly realize that one
JVC integrated sounds pretty much like another JVC
integrated, and pretty much like an Akai integrated as
well. It just happends that I don't like the sound of any
of them.


If Paul by "I don't like the sound of" you are referring to
your opinons, biases and prejudices, then I don't have a
problem.

If by "I don't like the sound of" you are referring to
actual component inherent sound quality, then you're
obviously speaking speculatively.


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